In our recent post discussing “The Six Principles of the Autonomous Enterprise,” we touched on all the key behaviors and technologies that must come together as smart leadership continuously seeks to refine the data it needs, in real-time, to be successful. We need to delve much deeper into the roles, traits, and responsibilities enterprise leaders must develop if autonomous enterprises are going to be effective in their emerging ecosystems:
A robust governance system embedded across all decision touchpoints guides the effectiveness of your autonomous enterprise
A strong governance capability has the talent, tech infrastructure, automation, and AI to deliver the data that will drive success with minimal manual interventions that impede progress and speed. The ultimate goal of an autonomous enterprise allows us humans to remove ourselves from some parts of the system so that we can make continuous improvements to the ecosystem as a whole.
Ultimately this is about machines making decisions where we previously had humans and removing humans from loops that don’t need humans anymore. Leadership must understand the data they need to be successful and assemble and govern the right system to deliver success. Hence great governance is about maximizing the ability of talent to understand and access data, make rapid decisions based on that data and have a seamless infrastructure that houses that centralized data, and embed an effective risk management framework. Bringing together those processes and interactions with trusted and scalable automation frees humans from slowing down decisions and operating effectively in fast-changing ecosystems.
What are the leadership roles needed to understand the data they need? How can we build the right internal teams and external partnerships to support an autonomous enterprise? And how can we design smart governance to manage key decisions faster with some degree of confidence? It really boils down to breaking down internal silos and designing leadership roles to drive better decisions and support talent.
These are the roles – and leadership traits – that will optimize the value from autonomous enterprise models
The Chief Executive Officer: The CEO should be the leader who drives the infinite mindset across the organization. He/she must continuously define the purpose of the organization and relentlessly drive a fearless collaborative culture that values stakeholder value beyond shareholder value. As a leader, it’s so easy to obsess with operational functions of the business during times of disruption or distress – in this case, a global pandemic – that it can create knee-jerk, often short-term decisions that could inherently damage your long-term vision, your business’ culture and your raison d’être. With no defined time horizon, no clearly-defined rules, and with players that may enter and exit at any time, the primary objective of an infinite game is quite simply to keep playing. The goal for businesses is to have the will and resources to stay in the game through thick and thin. And none more so that the current unpredictable and challenging business environment.
Having lived and worked through four recessions, I personally understand the rapid change in leadership mindset that can occur when a firm goes from peacetime and growth to one of survival and all-out war. According to author Simon Sinek, people look to leadership to serve and protect, to “set up their organizations to succeed beyond their lifetimes.” But in the modern landscape, most organizations place an unbalanced focus on near-term results that may ultimately prove to be self-defeating, like casting aside your umbrella in a storm because you haven’t been getting wet. In short, business is no finite endeavor. This pandemic lays plain for all to see the game we are really playing.
The CEO is the ultimate collaborator, forcing the change that is needed and balancing the desires of the various stakeholders (the board, key clients, key partners, the employees). His/her/their team to make this happen, must be responsible for the full gamut of their customers, employees, and partners, working with a transformational wizard to bring together the process and technology with the real innovation ingredient: the people. Taking people out of routine work that should be automated or digitized and refocusing them on responsibilities that require real innovation and cultural affinity is so valuable.
Chief Transformation Officer:Any transformation leader worth their salt must be able to drill an autonomous mindset into their teams and work out a plan to implement the right technologies to form the baseline to break down silos and centralize critical data.
This leader must link front to back office and ensure processes run smoothly across functions to deliver the data/outcomes the organization needs. This should ideally be someone who understands the challenges of enterprise operations and how to align them with the market-facing/client-impact areas of the firm. Forget the old GBS head / shared services head role, as this just has repeatedly failed to get out of the transactional back-office world and the “finance factory”. This person must oversee both technology and operations, understand the value of automation and AI, be able to design and implement change programs and work closely with the employee experience leader to eliminate the back office mindset from antiquated business functions into one that is aligned with the direction of the business.
Chief Customer Experience Officer: This is the leader who lives and breathes the world of the customers and obsesses with how to engage them as effectively as possible – right across the entire customer life-cycle – both with talented humans and autonomously where humans are not necessary. Ideally is someone who understands how to design customer interfaces, how to service customer needs leveraging both digital tools and physical support, and ensuring the entire employee base is unified around (and incentivized on) driving customer impact. In addition, the CCXO must ensure the marketing mindset is to communicate with the customer, educate the customer, and develop specific programs that have a real impact on driving customer engagement and business growth.
Chief Employee Experience Officer: Forget transactional HR, the employee experience leader is the person responsible for making the company a great, energizing place to work, where staff of all backgrounds, ages, experience levels cultures are energized by the values and desired outcomes of the firm. The CEXO must drive trust across managers and staff to embrace autonomous technologies and craft roles that maximize human interactions. Noone wants to be stuck in zombie roles in this environment where ambitious leaders demand value from their talent, delighting customers, colleagues and key partners. Never has there been a time when people skills are more important, supported by trusted and robust technologies and data infrastructures.
This individual must be the person who can manage the expectations of the board, the CEO, and the shareholders to create a company culture and values that everyone believes in. Moreover, the CEXO must be intimately involved in the creation and execution of training programs across the firm to attract talent who want to work for a company that will develop them, as well as establishing a culture and values they can identify with. This should ideally be a strong leader with broad experience in the business and staff development, who knows what it takes to be successful, and who understands how to motivate people beyond pure compensation. The best leaders today are also great people managers – and the CEXO role must be at the core of the business leadership, not some ancillary executive painting lip service and not having any real impact.
Chief Partner Experience Officer: As the OneEcosystem environment evolves, the need to collaborate with entities with common objectives across the entire customer value chain has never been so prominent. Partners are no longer just your suppliers. Suppliers are essential partners in delivering your goods/services. Still, the OneEcosystem looks at partners more holistically – partners in the ecosystem involved in providing the customer experience across the entire customer lifecycle.
An autonomous enterprise needs to function autonomously both internally and externally. Essentially, the OneOffice and OneEcosystem are effective when processes and interactions require fewer manual interventions and data can be accessed in centralized repositories. It requires leadership to have the ability to continuously refine the data it needs in real-time to be successful right across both internal and external ecosystems and the CPXO is the leader to drive this mindset into practice.
In the age of transparency, these roles must be codified to ensure accountability
It is not enough to provide a high-level description of the key roles that will govern an autonomous ecosystem – enterprises must codify the responsibilities of each one of them to ensure transparency when measuring their effectiveness.
As highlighted below, adherence to each principle of the Autonomous Enterprise comes with different responsibility levels across the leadership roles.
We believe the CEO should ultimately be accountable for understanding data needed for success. Thinking about data as an “ecosystem builder” requires a mindset and cultural change – if the CEO does not show the way, nobody will. The CEO’s mandate is to lead the way and be directly accountable for the overall performance of transitioning into a data-driven enterprise.
The Bottom-line: The old way of running businesses is fast eroding as we rethink what constitutes success and ambition. Bring on autonomous principles to drive the next wave of innovation
We launched the “HFS Enterprise Innovation Framework” in 2022 that enables organizations to survive (Horizon 1: Digital), thrive (Horizon 2: OneOffice), and ultimately lead (Horizon 3: OneEcosystem). One of the six distinct organization characteristics for enterprises to successfully create the OneEcosystem will be “autonomous processes” which allow firms to operate with less inefficiency in order to make faster decisions.
Did you ever think your enterprise could move to a 100% work-from-home environment with less than three weeks’ notice? This era of constant change has forced businesses to flex – vastly accelerating the OneEcosystem environment, dramatically cutting redundancies and improving processes at scale. Essentially OneOffice and OneEcosystem are effective when processes and interactions require fewer manual interventions and data can be accessed in centralized repositories. Hence leaders need to understand the data they need, have the right teams/partnerships to support them, and have smart governance in place to manage their decision points. The Autonomous Enterprise principles, if followed by smart, ambitious leaders, will enable the OneEcosystem mindset to prosper and provide the discipline and clean data needed to be effective.
There is a massive amount of change happening, and out of change comes real transformation. After years and years of complacency due to the relentless growth (and papering over the cracks of 2008), all of today’s organizations now finally have a burning platform to change how they operate globally. In fact, the autonomous platform is positively on fire!
When we look at the now-famous Cognizant CEO factory, probably the best-known of the bunch is Debashis Chatterjee (known simply as “DC” to everyone in the biz), who now finds himself leading the new $4.2bn powerhouse that is LTIMindtree. He’s also one of the calmest and easy-going guys you can hope to meet in this business.
DC originally took the helm at Mindtree in August 2019, and soon found himself contending with a “non-merger” as LTI decided to keep Mindtree separate, and then a pandemic followed. But that all changed in November last year when DC was announced as the first CEO of the newly (and finally) merged LTIMindree entity. So let’s hear directly from DC… what makes him tick and what’s next for the new 7th largest Indian-heritage service provider…
Phil Fersht – CEO & Chief Analyst, HFS: It’s great to see you again, DC. I mean, you’ve been around the IT services space since before the internet. Right?
Phil: I can also remember the world before the internet, as well, so you’re not that old 😁. But let’s hear a bit about you, DC. What gets you up in the morning these days? And, as you look back over your career, was running a multibillion-dollar IT services shop what you always wanted to do when you started?
DC: So, Phil, my background is I am a mechanical engineer, by education. I used to be a very avid sportsperson in my school and college days and played a lot of sports, including cricket, which is my favourite sport. And if I was not pushed hard, I would not have become an engineer; I would have rather liked to continue in sports.
And having done my mechanical engineering, I joined an automobile manufacturing firm, spent two years over there, then – and I’m talking about 1989 – that is when I got an opportunity to work in TCS, which was a great opportunity at that point in time. I think IT happened to me by accident because it was just that everybody said, “IT is the future,” so I jumped onto it, and since then, I haven’t looked back.
We went through various S-curves within the industry, whether it is the initial mainframe era, or the client-server, or the internet, and then, subsequently, cloud and Digital, and went through various inflection points as well, like Y2K and the global financial crisis in 2008, in which I was right in the middle of, because I was running the Financial Services vertical at that time. So I think it has been a pretty exciting journey.
And if you ask me what it is that I think, getting up in the morning now, is these two organisations coming together, erstwhile LTI and erstwhile Mindtree, creating LTIMindtree. I think this is the first time, and a very unique scenario, where two listed entities are coming together which are almost of similar sizes, and bringing these two organisations together, the entire integration, and ensuring that we can create value over a period of time – one plus one equals more than 2, you know. I am always thinking about how to make that happen as we go along. I mean, we already have some plans, but how do you ensure that the plans can translate into execution? That’s something which I’m always thinking.
And, to your point, running a multibillion-dollar IT services company – who would not like to do that?! Not that it was the desire when I was studying my mechanical engineering, but definitely, as I went along, I felt if you are in the industry, you need to learn how to run scale, and how do you manoeuvre at scale. And scale is not something that I have not done before, and it’s really not just the scale, it’s the question of how do you leverage the scale, and get the best out of that scale? And that’s what I have been trying to do for several years.
Phil: It must be tremendously satisfying, DC, having spent such a significant career working in some of the biggest IT services companies in the world, actually to run your own shop, and drive some areas that are special to you. I mean, I was an analyst for 15-20 years, and I always had a personal view on how an analyst firm should be led, and getting the opportunity to build my own company, and add my own stamp, was tremendous. So who influenced you along the way as you built your career, when you started to build this vision?
DC: Well, I think there are many people who influenced me; people whom I have met,Read More
Managed services markets in functions such as finance, procurement, and HR have matured over the years, and it’s increasingly hard to differentiate across service providers… most deliver via an effort-based FTE model; they all compete for the same pool of talent, and they all have similar issues controlling attrition in this environment. However, enterprise leaders are increasingly desperate for rapid access to centralized data to make critical decisions in a hugely unpredictable and complex business environment.
Helping firms access centralized data at speed is critical to growing value-based partnerships, and none more so in financial planning
Hence those providers engaging in financial planning and analysis (FP&A) managed services, where they are supporting these critical data and planning decisions for their clients, are getting much deeper into the high-value controllership areas for them. This is where the whole relationship shifts from one of providing effort to one of performance and purpose.
The HFS Strategic Finance Horizons report analyzes services provider capabilities shaping the financial planning and analysis industry and their proven capabilities to help their enterprise customers access critical financial data at speed. HFS assessed 13 major service providers’ prowess in the strategic areas of FP&A, based on the “Big 4” who are leading in some of the more specialized pieces of strategic finance and delivering managed services programs, and the F&A service providers with proven ability and scale to deliver FP&A work.
The new Horizon landscape (below) demonstrates the providers’ positions within the three horizons. Horizon 1 refers to those providers who have been able to drive functional FP&A transformation, Horizon 2 includes those who have reached the level of business transformation, and, Horizon 3 includes all those providers who have closed the gap and moved towards ecosystem transformation.
Agility and an evolving mindsetare key in this ever-changingfinance landscape
The last few years have shown us just how much enterprises need to focus on staying agile through uncertainty, change, and disruption. Financial planning and analysis strategy, technology, talent, and processes must evolve to keep up with finance leaders’ aspirations for helping the business navigate uncertainty and create long-term business value. In their quest for agility, we see finance and risk leaders engaging with third-party service partners not just on traditional FP&A activities but starting to move into strategic finance and performance management.Read More
Nothing dictates real secular change to enterprise operations than financial pressures, and we are rapidly arriving at a third major trigger that will lead to the evolution of many autonomous enterprises where leaders have no choice but to drag their operations out of the dark ages:
Trigger 1: 1995 – The Internet drives globalization. The advent of the Internet at the turn of the millennium drove the first major wave of globalization of business and operations.
Trigger 2: 2008 The Great Recession brings about mass low-cost offshoring of IT. In 2008… the Great Recession drove a 15-year wave of tremendous offshoring growth… based on lower-cost labor to slash costs.
Trigger 3: 2023 Inflation drives organizations to supplement or replace human labor with autonomous technologies. In 2023… wage inflation, recession, and people refusing to return to the office will drive a considerable wave of autonomous enterprises… based on technology to perform the tasks of humans to stay afloat.
What is an “Autonomous Enterprise”?
An autonomous enterprise is one whose leadership continuously seeks to refine the data it needs in real-time to be successful. Its governance capability ensures it has the talent, tech infrastructure, automation, and AI to deliver the data that will drive success with minimal manual interventions that impede progress and speed. The ultimate goal of an autonomous enterprise allows us humans to remove ourselves from some parts of the system so that we can make continuous improvements to the ecosystem as a whole.
Ultimately, this is about machines making decisions where we previously had humans and removing humans from loops that don’t need humans anymore. Leadership must understand the data they need to be successful and assemble and govern the right system to deliver success (see our Six Principles of the Autonomous Enterprise).
We are on the verge of the third significant trigger of business operations arbitrage – autonomous technologies at speed and scale
The advent of the Internet at the turn of the millennium drove the first significant wave of globalization of business and operations. Still, it wasn’t until the Great Recession of 2008 that sparked the first massive wave of IT offshore outsourcing saw the likes of Infosys, Cognizant, Wipro, and TCS enjoy enormous growth to become the multi-billion dollar firms they are today.
During the last decade, we have flirted with the advent of automation, where the rudimentary screen scraping, process, and system patches of RPA sparked the dreams of many CFOs and investors to “Automate the Enterprise.” The reality was that real progress with automation was never going to happen, while business unit leaders refused to make fundamental changes to their underlying processes and data. Plus, the fact that the global economy has been on a constant upward growth curve in recent years, and no one really drives painful, transformative change until economics forces them to.
Inflation-driven pressures will likely culminate in a huge wave of job reductions, sparking the demand for autonomous technologies to fill the void
In so many recent HFS roundtable conversations with enterprise leaders, there is one constant topic dominating proceedings: how to keep businesses functioning effectively when most staff are not willing to come to the office, when it’s impossible to coordinate complex process and workflow changes to the business, all while there is huge pressure to reduce inefficiencies, drive down costs and improve the quality of data.
In short, many businesses are limping out of the pandemic confusion, still struggling to pull themselves together, and in many cases, are slipping backward in terms of cementing their digital foundations and joining up key workflows across front-to-back offices.
Many organizations face significant staff reductions and have to figure out how to deliver on their operations and achieve their business outcomes with fewer people.
Operations leaders who cannot deliver on automation will become obsolete – it is now an expectation. Losing people will force smart managers to rethink how they can achieve more with less – you’ll simply have zero choice but to act. You’re running a finance department of 500 people, which is reduced to 250. How do you get stuff done now? You’d better reconfigure how processes work so you can take advantage of automation that can interact – via voice and digital – with self-learning capabilities that don’t need constant human supervision.
On the flip side, less people will make it easier to identify areas that demand urgent changes, and as they identify the critical data they need to be effective: do they know what their customers’ needs are? Is their supply chain effective in sensing and responding to these needs? Can their cash flow support immediate critical investments? Do they have a handle on your employee morale and performance?
Where technology can deliver routine tasks via simple automation and self-learning AI is becoming critical. HFS is using the team “digital employees” to describe how smart bots can function autonomously, can respond to both voice and digital interactions, can develop both short and long-term memories, can genuinely replace or supplement human activities to deliver workflows and processes that can provide the data company leaders need – at speed and at scale.
Automation is the leading tech investment being made among Global 2000 enterprises
10 years since HFS introduced RPA to the industry (see link), and we’re finally focusing on automation as a value-lever that drives business outcomes, as opposed to mere cost takeout in the back office.
The pandemic has shifted the automation focus from creating efficiencies in the back office to delivering immediate business impact, where talent shortages can be overcome, where digital workflows can operate despite broken supply chains, and where businesses can find new opportunities in their virtual and hyperconnected ecosystems.
Our recent pulse data of 602 enterprises proves beyond doubt that automation is the number one initiative currently underway to support enterprises in meeting their strategic priorities:
Automation is a discipline and a mindset
Automation is becoming so increasingly important to businesses as it helps solve so many of these endemic problems being caused by labor shortages, wage inflation, and poorly integrated systems, workflows, and processes. Simply put, if you get better at automating, you’re solving a lot of these other problems at the same time.
Smart business leaders have realized that automation is a mindset and a discipline that needs to be ingrained into every business practice. It is not why we do things; it’s how we do them. Automation makes what we have function effectively without needing constant human attention and manual workarounds. And the better we understand automation, the more autonomous it can become to drive genuine artificial intelligence interactions and processes in the future. AI and automation are becoming increasingly synonymous as we figure out how automation can really work within a business operation.
If there’s one thing the pandemic taught us, it’s been the necessity to re-think processes to get the data; what should be added, eliminated, and simplified across our workflows to source this critical data. And there is simply no option but to plan to design processes in the cloud using web-architected applications. In this virtual economy, our global talent must come together to create a borderless, completely digital business ecosystem where we can connect with other organizations that share common goals and purposes. This is the true environment for real “digital transformation” in action.
The Bottom-line: Most enterprises are only at the start of the real autonomous journey
As we reflect on our research covering over 500 automation leaders of major enterprises, what hits us the most is that 70% admit they are still novices. It seems the more they learn, the more they realize they need to know. We’re only at the start of a long journey for the majority of today’s ambitious organizations, and selecting the right partners along the way to help them design, implement and learn from automations across their businesses is so important. As one CIO delightedly pointed out to me recently: “I’ll keep finding automation ’till I die”… now that’s the attitude that is changing the whole approach to automation as the new IT mindset.
There is major rethinking taking place for 2023, where many firms are simply struggling to navigate this current maze of complexity and cost. The Autonomous Enterprise vision is where the survivors are looking, but getting there requires fewer people, politics, resistance to change, and great partnerships…
It’s 2023, and there are no excuses left for enterprise leaders to figure out how to run their organizations as autonomously as possible.
Definition: What is an “Autonomous Enterprise”?
An autonomous enterprise is one whose leadership continuously seeks to refine the data it needs in real-time to be successful. Its governance capability ensures it has the talent, tech infrastructure, automation, and AI to deliver the data that will drive success with minimal manual interventions that impede progress and speed. The ultimate goal of an autonomous enterprise allows us humans to remove ourselves from some parts of the system so that we can make continuous improvements to the ecosystem as a whole.
Ultimately this is about machines making decisions where we previously had humans and removing humans from loops that don’t need humans anymore. Leadership must understand the data they need to be successful and assemble and govern the right system to deliver success.
The Six Principles of The Autonomous Enterprise
So we have put together Six Principles that leaders need to adopt to ensure they can keep refining the autonomous abilities if their enterprise within its business ecosystem and adjacent ecosystems:
Your leadership must understand the data needed for your enterprise to be successful.
Your teams must know your processes and interactions in digital detail and have a continuously updated audit trail of these digital interactions and processes.
You must have the right infrastructure to breakdown the silos of data across your enterprise and its ecosystem.
You must ensure a robust and scalable automation capability that is trusted both internally and externally.
Artificial Intelligence (ML, deep learning, and decision engines) must continuously find patterns in your data to keep you ahead of your market.
You must establish a robust governance system embedded across all decision touchpoints to ensure the effectiveness of your autonomous enterprise.
Stay tuned for Part II where we delve into the sixth principle of how to assemble and govern the right blend of talent, tech, automation, and AI to deliver looping success…
We’re still clueless about sustainability. Key people, in key organizations, in key rooms, still need help with contextualizing their roles and where to best spend their time and energy. Here we run over some musing across the global context, sustainability services, the energy and utilities industries, and the supply chain. If you make it to the bottom, you’ll find the last sources of optimism in the hand of both services firms and the increasingly powerful coalitions of the willing, hoping to overcome the failures of politics and apologize later.
In 2023 we’ll continue to get little to no help from politics or changes in consumer behavior
COP28, the UN climate summit series’ next installment in the UAE, will likely be as useless as COP27. See our recent take on why mediocrity at COP27 was worse than its implosion. Organizations we speak with are often lacking in materiality assessments and the roadmaps that need to encompass the whole global sustainability context. Too often their energy is easily diverted to the latest problem.
Are we going to hit a 1.5-degree temperature rise in 2023?
Probably not. But in a few years, probably yes. The Economist has a good take on the all-but-death of the Paris Agreement target.
Will we see climate related disasters and system tipping points?
Almost certainly on both fronts. Here’s a good Guardian compilation of an Oxford University summary. Floods, fires, droughts, and more will continue to reinforce that policy, and the public cannot move at the speed and systems-level required to tackle climate change and the global sustainability context covering all environmental, social, and governance (ESG) factors. It’s already too late for so many. It’s now a question ofRead More
It’s hard to believe that ten years have passed since HFS introduced RPA to the industry. Now we’re finally focusing on automation as a value lever that drives value beyond cost reduction and productivity gains. However, we still have a long journey ahead, with two-thirds of automation leaders self-declaring themselves as novices.
The economic conditions in 2023 will put automation in the hot seat, and expectations are on operations leaders to roll out automation initiatives
In short, the pandemic was good for automation technologies because enterprises used them to fix immediate problems that were impeding organizations, whether it was adding chatbots to fix CX shortages, plugging gaps in broken supply chains, fixing government loan systems to save struggling businesses, pulling together critical data across healthcare value chains, etc. RPA created a narrative that was eons away from what it really did, but the real solution to automation’s problems is its role in helping organizations out of a hugely complex economy in 2023, with companies laying off and being forced to automate to keep the wheels on.
Far too many firms have been fat and happy and inefficient for years, and their chickens will finally come home to roost in this challenging market. Moreover, the utter confusion being created with so many staff working from home is becoming a huge farce… just watch companies ordering staff back to the office in January (the pendulum has swung). This is a moving dynamic…
There will likely be a lot of layoffs in Q1 next year, so firms will be forced to do more with less… will they be able to? Bad managers will use work-from-home as an excuse and either force staff back in or lay them off. The net result will be a lot of confusion and complexity, and firms will find themselves short-staffed and needing a lot of help. Automation will be expected to fill the labor void by many firms, especially as it tops investment levels in organizations, and operations leaders are now expected to be able to drive automation projects. There are enough case studies out there, and there are no more excuses – get automating and do it quickly!
The need for partners to drive automations deep into the enterprise is ramping up fast
So one thing is clear, most organizations will need a lot of help to roll out real automations that perform more than basic RPA – they need to evaluate automation and AI technologies across the board to move their organizations forward across our three Horizons:
Horizon 1: Ability to drive functional optimization outcomes through cost reduction, speed, and efficiency
Horizon 2: Enablement of the OneOffice model of enterprise-wide end-to-end automation
Horizon 3: Ability to drive synergies and completely new sources of value across the business ecosystem
To find out, we looked at 18 automation service providers and management consultancies across these three horizons:
Providers were assessed across a series of four criteria
The Why: Value proposition, including market vision and strategy, and competitive differentiators;
The What: Execution and innovation capabilities, including breadth and depth of automation services, technology capabilities, proprietary tools and solution accelerators, patents and intellectual property, the strength of their talent pools, and the strengths of their ecosystems;
The How: Go-to-market strategy, including relevant acquisitions and other investments, co-innovation and collaboration approaches, industry and geographic client portfolio, creative commercial models, and thought leadership and market education.
So What: Market and client impact, including size and growth automation practice, nature of value delivered, and voice of the customer
The 18 service providers covered in this report include, alphabetically, Accenture, Bain and Company, Capgemini, Cognizant, Deloitte, EXL, EY, Genpact, HCLTech, IBM, Infosys, KPMG, NTT Data, PwC, TCS, UST, Virtusa, and Wipro.
HFS subscribers can download the report here (available free for a limited time).
In October 2022, HFS said goodbye to the Top 10’s and welcomed HFS Horizons, a forward-lookingconstruct to evaluate service providers. Our first industry-focused horizon report is the healthcare payer service providerreport that was published inNovember 2022. This report helps healthcare enterprise buyers make high-confidence buying and partnering decisions in the context of the specific challenges they are attempting to address.
Note: All service providers within a “Horizon” are listed alphabetically
A healthy list of 21 service providers evaluated
The service providers were evaluated across four dimensions – Why, What, How and So What – to arrive at a comprehensive conclusion categorizing service providers into three horizons: supporting Functional Transformation (Horizon 1), driving Enterprise Business Transformation at scale (Horizon 2), and leveraging deep healthcare expertise to craft Domain-Specific Transformation (Horizon 3).
The HFS Horizons report is about matching service provider capabilities to enterprise buyer needs
This study aids health plans, government agencies, and self-insured employers to understand the forward-looking capabilities that service providers will bring to bear.
The Healthcare Horizon report is an effort to help healthcare enterprise buyers evaluate service providers fit for the challenges they face as the market needs evolve. It shines a light on where the puck will be for enterprise buyers and the ability of service providers to meet the puck where it will be instead of where it is.
Unlike a ranking study, each Horizon reflects a set of capabilities aligned to a set of industry challenges that require addressing. It’s a practical tool for making high-confidence buying and partnering decisions.
The Healthcare Horizons Report boldly indicates how healthcare funding is shifting and its implications for service providers
Funding for healthcare in the US has been shifting from fully funded commercial insurance to self-insured employer and government programs steadily for several years. Governments (state and federal) and large employers have become the largest underwriters of medical risk.
Consequently, traditional health insurance companies are changing from financial institutions to service providers. This fundamental shift will continue to strengthen co-opetition between health plans and service providers, requiring a different solution portfolio and go-to-market to address the evolving needs of a reconfigured market.
Healthcare provider choices are driven by health insurance. In 2020, enrollment in self-insured employers surpassed enrollment in plans underwritten by health insurers. Self-insured employers will likely seek direct-to-provider contracts both for primary and acute care to drive improved employee productivity instead of just reactive care. The shift in this market dynamic could make a positive change in aligning HCPs to health vs. just volume-driven sick care.
Vertical integrations mean new opportunities for service providers
The shifting markets are forcing healthcare enterprises (health plans and providers) and new entrants to create new business models that require a new level of vertical integration. Integrated delivery networks or IDNs, such as Kaiser Permanente and UPMC, have shown that the power of vertical integration through proliferation across the healthcare ecosystem has been limited.
However, a new wave of vertical integration is reimagining how synergies could redefine the value proposition. This will require service providers to rethink their solution portfolio and go to market.
The Healthcare Horizons report includes service providers with heritages across IT services, BPO, consultancy, and healthcare
The 21 service providers covered in the healthcare horizon report, alphabetically, are Accenture, Capgemini, Cognizant, Deloitte, EMIDS, EXL, EY, Firstsource, Genpact, HCL, Infosys, KPMG, Mphasis, NTT DATA, Optum, PWC, TCS, UST, Virtusa, Wipro, and WNS.
This report includes detailed profiles of each service provider, outlining their placement, provider facts, as well as detailed strengths and opportunities.
HFS subscribers can download the report here (available free for a limited time).
As HFS reflects on last week’s AWS re:Invent event, it becomes increasingly clear that the firm could lose steam as the migration to the cloud, as a technology platform, gives way to the cloud’s role in making data a business asset.
While AWS’ growth numbers are still holding up, there could be significant changes on the horizon as Google Cloud Platform (GCP) makes up lost ground with its approach to a data-centric cloud environment. In addition, cool kids on the block like Snowflake and Databricks are changing the narrative from commodity cloud to data-driven cloud.
The fact that AWS forced HFS to digest these proceedings online speaks volumes for AWS’ preference to have only analysts in-person who will sing their praises, repeat their rhetoric, and refrain from challenging them. Why risk analysts who dare to talk to enterprises and question the logic of where (and why) they are spending vast amounts of their money with a half-baked cloud vision?
If you move your existing crap into the cloud, you’ll end up with even worse crap… and less than 50% of cloud native transformations are currently successful
AWS continues to cash in by bolstering its commodity cloud offerings and pouring funds into a morass of new products. The result is the significant complexity for enterprise customers to navigate this portfolio and piles pressure on them to seek out increased support from partners with both domain and data experience.
Our research shows that migrating to the cloud is costing enterprises many billions a year, and that cost continues to rise as many enterprises move too fast and fail to fix their underlying data infrastructures. Throw in the massive wage hikes, attrition and skills shortages in the tech space, and the cost of migrating your critical data into the cloud becomes unconscionable, especially at a time when most CFOs are freezing spending in anticipation of a very challenging economic period.
Net-net, you can’t migrate processes and workflows that don’t get you the data you need until you’ve fixed them first. If you move your existing crap into the cloud, you end up with even worse crap, and you just wasted a lot of time and money in the bargain. And you don’t even need to survey what enterprise buyers are spending – you just need to examine the huge growth numbers enjoyed by the majority of consultants and IT services providers in recent years, cashing in on rushed and poorly prepared cloud migrations.
The move away from “all in on hyperscalers” is more a threat to AWS’s bottom line than it is to either of its notable competitors, Azure or Google Cloud, as hosting data, facilitating compute, and managing web storage is now a commodity whose costs-to-ROI is being questioned (although nicely) not as the “move to the cloud” but the “move to hybrid.”
As noted in HFS’s recent Cloud Native Transformation Horizons study, “The buy side is struggling to capture the value of their cloud investments, as very few enterprise customers have a well-defined cloud transformation strategy at an organizational level, which can lead to transformations done in silos.” The results are showing that less than 50% of cloud native transformations are a success…
HFS views Google Cloud Platform as a refreshing future for enterprises considering their cloud migration more strategically to address data in the domain context
The “Cloud” is quickly becoming a commodity platform. Adopting a cloud-native mindset is about leveraging multi and hybrid cloud solutions to deliver business outcomes, empowering employees, customers and partners, all the while managing costs. While AWS is the current leader in the hyperscaler market, it’s clearly feeling the pressure as GCP closes the gap.
HFS has repeatedly been documenting the importance of data. From “forget apps, it’s about the data” to a view on “data is your strategy,” and on modernization, there are many articles where we’ve done deep dives into the importance of data, automation, analysis, visualization, implementation, governance, and partnering to deliver results. We firmly believe that data is crucial to building, maintaining, and growing a robust, resilient ecosystem.
In fact, we flagged this in our HFS Pulse data from early 2021, where Global 2000 firms cited databases as the top workload being moved to the cloud:
The importance of data isn’t new… it’s your business strategy more than ever
To be a truly autonomous organization that operates in the cloud, the principles of OneOffice hold truer than ever: workflows need to execute in real-time between customers and employees – and engage partners in your ecosystem. OneOffice is about understanding and discovering the data you must have to win in your market – right now in real-time – as the market environment keeps changing.
Google has been an advocate of data for years and tied this theme from their data center to Google Apps used by millions of firms. Yet, if a vendor (ahem, AWS) believes they can win with data, they really must improve how they tell their story if they want to expand their services and revenue opportunities further. And this is where we see GCP closing in fast on AWS – hence the attempt at re:Invent in which AWS attempted to re:Position itself as a data leader as well, which is so critical to the datacycle that drives OneOffice:
Five steps you must take to get the data you need into the cloud
Moving data into the cloud has to be both a business transformation and a technical exercise. You can’t keep separating the worlds of business and IT any longer if you want your workflows to be executed autonomously in the cloud. Business executives must identify the data they need to be effective in making decisions and work with their IT counterparts to build a data structure that can be effectively migrated and operated in a cloud environment:
Get data to win in your market. This is where you must align your data needs to deliver on business strategy. This is where you clarify your vision and purpose. Do you know what your customers’ needs are? Is your supply chain effective in sensing and responding to these needs? Can your cash flow support immediate critical investments? Do you have a handle on your staff attrition?
Re-think processes to get this data. Then you must re-think what should be added, eliminated, or simplified across your workflows to source this critical data. Do your processes get you the data you need from your customers, employers, and partners?
Design your new workflows to be executed in the cloud to deliver the data. There is simply no option but to have a plan to design processes in the cloud over three-tier web-architected applications. In the Work-from-Anywhere Economy, our global talent has to come together to create our borderless, completely digital business. This is the true environment for real digital transformation in action. This means you can’t migrate processes that don’t get you the data you need until you’ve fixed them first. If you move your existing crap into the cloud, you end up with even worse crap and just wasted a lot of time and money into the bargain.
Automate processes and data. Automation is not your strategy. It is the necessary discipline to ensure your processes provide the data – at speed – to achieve your business outcomes. Hence you have to approach all future automation in the cloud if you want your processes to run effectively end-to-end. This is where you need to ensure connectors, APIs, patches, screen scrapes, and RPA fixes not only support a digital workflow but will scale in the cloud. Many of these patched-up process chains become brittle and fall over in a scaling situation if the code is weak. We’ve seen billions of dollars wasted on botched cloud migrations in recent years because underlying data infrastructures were not addressed effectively, and bad processes became even less effective or completely dysfunctional.
Apply AI to data flows to anticipate at speed. Once you have successfully automated processes in the cloud, it is easy to administer AI solutions to deliver at speed in self-improving feedback loops. This is where you apply digital assistants, computer vision, machine learning, augmented reality, and other techniques to refine the efficacy of your data. AI is how we engage with our data to refine ourselves as digital organizations where we only want a single office to operate with agility to do things faster, cheaper, and more streamlined than we ever thought possible. AI helps us predict and anticipate how to beat our competitors and delight our customers, reaching both outside and inside of our organizations to pull the data we need to make critical decisions at speed. In short, automation and AI go hand in hand… AI is what enables a well-automated set of processes to function autonomously with little need for constant human oversight and intervention.
Being a leader in data is more than having lots of storage, compute, and add-on SKUs
Connecting data workloads across multi and hybrid clouds, cloud data warehouses, data lakes, and applications is the world we live in. the orchestration of these is crucial and a focal point of projects from the Cloud Native Computing Foundation to Kubernetes.
While both firms are active in the CNCF and have solutions that support K8S, AWS is the more clunky of the two. To be successful, data must flow across internet, storage, and servers; thus, the configuration must be simple to implement and maintain. AWS growth is its own weakness here as tools like managing IP domains to microservices, containers, and Kubernetes are being driven by Google’s efforts ahead of AWS.
The orchestration of data is a prime example. With regards to orchestration, the EKS (AWS version of Kubernetes) has been considered so poor that firms like Red Hat have come to their customer rescue with Red Hat Open Shift for AWS (ROSA). AWS continues to improve its EKS, but it is substantially behind GCP and its customers are leaning on third parties to deliver these solutions.
Domain experience is key and AWS needs partners to deliver this – and they may be disintermediated as a result
AWS is the first to market leader. Our hat is off down for the efforts they put into developing the hyperscaler market. But as the pioneer, much like every innovator they now have a dilemma of how to stay in front while watching both Azure and GCP create more functional solutions for enterprise customers to build their business upon. As GCP continues to ramp the number of certified engineers and experts in core cloud-native solutions like Kubernetes, AWS has found it critical to shoring up partnerships to attempt to lock out the young Turk.
However, while enabling partners to develop and improve on your technology and bring its products in larger domain and ecosystem projects, it opens the door to being disintermediated. A case in point that AWS to rushing to address is AWS outposts. With the rise of hybrid Cloud and the extension of public Cloud, AWS is seeing customers retreat from its hyperscaler services to diversify and reduce costs. Integration firms are partnering with competing compute and data solutions to bring in stateless cloud solutions optimized for the customer domain, not the IT.
We see AWS as a very strong player when it comes to partnerships from a revenue perspective, but GCP is emerging when data is top of mind for enterprises. Partners are leveraging the AWS brand to boost revenues as the complexity of AWS is a challenge for even the most sophisticated organization. With the industry reaching this cloud-data pivot point, the door is wide open for these partners to increase their revenue streams by offering domain expertise, complex integration, and long-term support services. AWS’s own industry solutions lack real drawing power without these partners. And some partners, like IBM, bring tools such as Red Hat Open Shift for AWS (ROSA) that are sorely needed by customers to orchestrate hybrid and multi-cloud solutions.
Data holds the keys to cloud supremacy and AWS knows they are in for a real fight with Google
In Adam Selipsky’s keynote, he brings up the importance of data early (about 15 minutes in for those watching at home). Based on his keynote, “data is the center applications, processes, [and] business decisions. And is the cornerstone of almost every organization’s digital transformation.” Going on to the need for tools, integration, governance, and visualization. Much like what HFS has proposed (and re-iterated recently) as data being your strategic level for everything you do.
In the keynote, Mr. Selipsky spent most of his time on AWS investments across the data modernization value chain of data storage, compute, load management, analytics, governance, and visualization. Several key products to manage, visualize and forecast data were announced; while these are much needed to round out the AWS data story, they also add more SKUs that customers will need help determining how these new solutions map to their ability to implement, train, and manage.
Organizations are being asked to put all their eggs in one basket to take advantage of AWS’s data story as painted by Adam and Swami Sivasubramian (AWS VP Data & ML). And in many cases, while AWS has the first mover advantage, the power, and tools of Google’s Big Query, Cloud Dataflow, and Data Studio.
Key messages from Google Cloud Next that must have shaken AWS
At Google Cloud Next, they announced strategic partnerships with Accenture and HCLTech. These partnerships build on how services firms can merge hyperscalers’ capabilities with the domain-centric intellectual property of services providers. Customers like Snap, T-Mobile, and Wayfair continue to put their trust in Google Cloud’s expertise in data analytics, artificial intelligence, and machine learning and expand the ongoing partnership. Further, Rite Aid signed up with Google Cloud for a multi-year technology partnership that will help its customers with expanded and personalized access to the company’s pharmacists, an enhanced online experience, and intelligent decision-support systems—powered via Google Cloud technologies.
Google is very clear on how data is core to its DNA, and the firm is bringing its knowledge and expertise to market with partners. In fact, many of the mergers and acquisitions of IBM, Accenture, Capgemini, and more are of firms with GCP practices. Data and multi-cloud, delivered through proven user applications to the masses, is clearly the future to democratize decision-making in ways that companies only dreamed up. Making data easy to find and action is bringing velocity to Google – and the likes of Databricks and Snowflake – that can’t be ignored.
We listened to AWS: what we liked and didn’t like
What fell flat (or at least was left in ambiguity):
Cloud costs are important. In Adam Selipsky’s keynote, he made a show of AWS’s focus on customer, domain, and ESG values. However, he quickly moved to the defensive as less than 10 minutes in he began arguing the Cloud is cheaper to run on than traditional data centers. Citing company examples like Carrier, Gilead, and others and their savings. While these data points may be valid in aggregate, there is little detail or scope on how or what costs were saved – e.g., were they supporting or mission-critical workloads or solutions? The proof is in the data, and that really wasn’t on offer.
Data is critical, and the lens to analyze hyperscalers is changing completely. AWS wants to be your data partner – but hasn’t really appreciated the complexity of migrating that data to the solutions. Hence the need to lean on the development of a more robust partner ecosystem.
Millions of choices and crazy product fragmentation. AWS is becoming Baskin-Robbins, with more flavors and choices. Hey, it’s great to have a choice, but there comes a point with too much choice, too many overlapping features and a need to carefully evaluate the pros and cons of each becomes more of a burden than a blessing. For instance, AWS offers 13 databases (8 purpose build (proprietary) and five relation data engines), 12 analytics tools, and 19 AI/ML SKUs! AWS’s increasingly fragmented product catalog is creating challenges for customers and their partners to implement and support.
AWS focused on technical outcomes, leaving business cases to customers and partners. From Elastic Fabric Adapters to Graviton chips to Redshift product names made up a cluster of new choices that will need to be educated, trained, and validated. AWS focused on what they must buy, not why they are building these.
AWS’s data democratization story comes up short. Amazon DataZone was pitched as a solution for data users across an organization to deliver market insights. While creation, tagging and governance were strengths, the usability and collaboration components lacked the functionality of Google’s Looker, which offers broader integration with more industry solutions and visualization tools.
What we liked and feel AWS can continue to build on:
AWS recognizes that data is the cornerstone. re:Invent has joined the data is critical bandwagon. AWS is getting much sharper on its messaging about how it aspires to be a trusted partner in developing solutions for developing data as an asset in the Cloud. With AWS Aurora, they are taking the fight to Microsoft and Oracle, pushing open-source SQL (PostgreSQL-based) solution that has the functionality with lower overhead and costs.
AWS is improving the marketing of its portfolio to partners. AWS celebrated its software and services ecosystem. This is needed, given how complex the AWS product and marketplace have become. Customers need their trusted partners to help them sort through the AWS offerings to help them choose the right solution for their business.
Data security got major props. AWS has realized to be a valid place for data, it needs robust security. It has offered some interesting solutions about AWS Security Lake with both its own and partner (Cisco, Snowflake, Palo Alto Networks, etc.) solutions. But how will these security solutions allow for multi-cloud solutions?
AWS is becoming a marketplace for cloud solution. As Siemens showed in their part of the keynote, they recognize AWS reach to resell their software solutions. By moving their code to AWS, they can drive new revenues streams and provide the market with industry-centric solutions.
Supply chain tools and insights. AWS Supply Chain Insights is a very interesting solution to see how your ecosystem is working to address data from multiple companies into a singular view for businesses to address inventory, supplier management, and customer outcomes.
The Bottom Line: Objects in the rear-view mirror, may appear closer than they are. In AWS’s rear-view mirror is Google…
As AWS pivots its story from scale, storage, and cloud servers to data the firm further validates Google’s relentless focus on data for the past several years.
AWS has ridden the cloud wave into this very dominant position in the market, but as we have seen, this race has many more cycles to run as we face a deep European recession and an uncertain US market as enterprises grapple with multiple headwinds. Cost is king, and the focus will be on data-driven value as opposed to mere commodity compute. AWS must avoid resting on its laurels if it’s going to keep the likes of Google from eating into its market share with its deep, deep resources and second-mover advantage.
The complexity and large number of choices the average user must now navigate to deploy, manage, and govern AWS investments is creating an opportunity for customers and the global IT Services market to reinvest in their relationships with Google to drive data, multi-cloud orchestration, and user application integration.
Honestly, there was lots to unpack at re:Invent. We, like millions, peered in for hours on the internet, and saw some very cool innovations coming from AWS. However, once compared with a quick ‘google’ to those of Azure or GCP, it lost a fair bit of its innovative luster.
Look out AWS, GCP is coming for you. And it’s coming fast in this choppy, demanding, data-obsessed, and hyperconnected business environment.
We’ve been trying to define automation and AI for over a decade now, and – let’s face it – they’re heading for the mush-bucket of sexy technologies that promised a lot, but most people failed to understand what they really did… or how to exploit them. And not all of them actually worked. Plus, when I recently heard a Wall St analyst discussing the stock performance of UiPath’s “automation equipment,” I realized even the money guys have zero clue what automation in the workplace really entails; yeah, we’re in big trouble…
So how do we define how to create a nimble, autonomous organization in today’s post-hype market?
When HFS coined OneOffice in 2016, we inadvertently defined how businesses would have to operate… we just didn’t realize it would take another six years, a pandemic, rampant inflation, and a catastrophic European war to create the burning platform where enterprises have to be virtual, autonomous and much more cost-conscious, with capable talent and partners to help them function in these emerging business ecosystems:
“HFS in 2016: The onset of digital and emerging automation solutions, coupled with the dire need to access meaningful data in real-time, is forcing the back and middle offices to support the customer experience needs of the front. Consequently, we’re evolving to an era where there is only “OneOffice” that matters anymore, creating the digital customer experience and an intelligent, single office to enable and support it
Today’s college graduates are simply not coming out of school willing to perform mundane routine work: operations staff proactively need to support the fast-shifting needs of the front office. So the focus needs to shift towards creating a work culture where individuals are encouraged to spend more time interpreting data, understanding the needs of the front end of the business, and ensuring the support functions keep pace with the front office.”
By 2022 all we have really done is understand better how to align your employees with the needs of your customers – and your employees have also become your most important customer. To be a truly autonomous organization, the principles of OneOffice hold truer than ever: workflows need to execute in real-time between customers and employees – and engage partners in your ecosystem (you can download our OneEcosystem vision here).
We need to understand that data is the strategy and how the data cycle works to get us ahead of our markets. Here are five steps we must take:
Get data to win in your market. This is where you must align your data needs to deliver on business strategy. This is where you clarify your vision and purpose. Do you know what your customers’ needs are? Is your supply chain effective in sensing and responding to these needs? Can your cash flow support immediate critical investments? Do you have a handle on your staff attrition?
Re-think processes to get this data. Then you must re-think what should be added, eliminated, or simplified across your workflows to source this critical data. Do your processes get you the data you need from your customers, employers, and partners?
Design your new workflows to be executed in the cloud. There is simply no option but to have a plan to design processes in the cloud over three-tier web-architected applications. In the Work-from-Anywhere Economy, our global talent has to come together to create our borderless, completely digital business. This is the true environment for real digital transformation in action. This means you can’t migrate processes that don’t get you the data you need until you’ve fixed them first. If you move your existing crap into the cloud, you end up with even worse crap and just wasted a lot of time and money into the bargain.
Automate processes and data. Automation is not your strategy. It is the necessary discipline to ensure your processes provide the data – at speed – to achieve your business outcomes. Hence you have to approach all future automation in the cloud if you want your processes to run effectively end-to-end. This is where you need to ensure connectors, APIs, patches, screen scrapes, and RPA fixes not only support a digital workflow but will scale in the cloud. Many of these patched-up process chains become brittle and fall over in a scaling situation if the code is weak. We’ve seen billions of dollars wasted on botched cloud migrations in recent years because underlying data infrastructures were not addressed effectively, and bad processes became even less effective or completely dysfunctional.
Apply AI to data flows to anticipate at speed. Once you have successfully automated processes in the cloud, it is easy to administer AI solutions to deliver at speed in self-improving feedback loops. This is where you apply digital assistants, computer vision, machine learning, augmented reality, and other techniques to refine the efficacy of your data. AI is how we engage with our data to refine ourselves as digital organizations where we only want a single office to operate with agility to do things faster, cheaper, and more streamlined than we ever thought possible. AI helps us predict and anticipate how to beat our competitors and delight our customers, reaching both outside and inside of our organizations to pull the data we need to make critical decisions at speed. In short, automation and AI go hand in hand… AI is what enables a well-automated set of processes to function autonomously with little need for constant human oversight and intervention.
Bottom-line: You can’t get the data you need if you don’t have the people, partners, processes, technology – and desire to change – to make this possible
You can lead a horse to water, but can you get it to drink? OneOffice is about understanding and discovering the data you must have to win in your market – right now in real-time – and in the future – as the market environment keeps changing. Then you need to make your data ubiquitously available, accessible, and mineable – embedding a mindset into your leadership to inspire your people to work together to create an organization that can flip its business model to exploit these seismic market changes. You can’t get the data you need if your critical data is not in the cloud and you don’t have the people, partners, processes, technology – and desire to change – to make this possible.
And perhaps most importantly, you need to accept that your star employees are your biggest customers. Without them, you won’t stand a chance of dragging your decrepit processes and data infrastructures out of the dark ages.
